YongKiat Wee1, TianFang Wang1, Yining Liu2, Xiaoyan Li3, Min Zhao4. 1. School of Engineering, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Queensland 4558, Australia. 2. The School of Public Health, Institute for Chemical Carcinogenesis, Guangzhou Medical University, 195 Dongfengxi Road, Guangzhou 510182, China. 3. Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung & Blood Vessel Disease, Beijing, China. 4. School of Engineering, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Queensland 4558, Australia. Electronic address: mzhao@usc.edu.au.
Abstract
AIM: There has been limited research on CNVs in oncogenes and we conducted a systematic pan-cancer analysis of CNVs and their gene expression changes. The aim of the present study was to provide an insight into the relationships between gene expression and oncogenesis. MAIN METHODS: We collected all the oncogenes from ONGene database and overlapped with CNVs TCGA tumour samples from Catalogue of Somatic Mutations in Cancer database. We further conducted an integrative analysis of CNV with gene expression using the data from the matched TCGA tumour samples. KEY FINDINGS: From our analysis, we found 637 oncogenes associated with CNVs in 5900 tumour samples. There were 204 oncogenes with frequent copy number of gain (CNG). These 204 oncogenes were enriched in cancer-related pathways including the MAPK cascade and Ras GTPases signalling pathways. By using corresponding tumour samples data to perform integrative analyses of CNVs and gene expression changes, we identified 95 oncogenes with consistent CNG occurrence and up-regulation in the tumour samples, which may represent the recurrent driving force for oncogenesis. Surprisingly, eight oncogenes shown concordant CNG and gene up-regulation in at least 250 tumour samples: INTS8 (355), ECT2 (326), LSM1 (310), DDHD2 (298), COPS5 (286), EIF3E (281), TPD52 (258) and ERBB2 (254). SIGNIFICANCE: As the first report about abundant CNGs on oncogene and concordant change of gene expression, our results may be valuable for the design of CNV-based cancer diagnostic strategy.
AIM: There has been limited research on CNVs in oncogenes and we conducted a systematic pan-cancer analysis of CNVs and their gene expression changes. The aim of the present study was to provide an insight into the relationships between gene expression and oncogenesis. MAIN METHODS: We collected all the oncogenes from ONGene database and overlapped with CNVs TCGA tumour samples from Catalogue of Somatic Mutations in Cancer database. We further conducted an integrative analysis of CNV with gene expression using the data from the matched TCGA tumour samples. KEY FINDINGS: From our analysis, we found 637 oncogenes associated with CNVs in 5900 tumour samples. There were 204 oncogenes with frequent copy number of gain (CNG). These 204 oncogenes were enriched in cancer-related pathways including the MAPK cascade and Ras GTPases signalling pathways. By using corresponding tumour samples data to perform integrative analyses of CNVs and gene expression changes, we identified 95 oncogenes with consistent CNG occurrence and up-regulation in the tumour samples, which may represent the recurrent driving force for oncogenesis. Surprisingly, eight oncogenes shown concordant CNG and gene up-regulation in at least 250 tumour samples: INTS8 (355), ECT2 (326), LSM1 (310), DDHD2 (298), COPS5 (286), EIF3E (281), TPD52 (258) and ERBB2 (254). SIGNIFICANCE: As the first report about abundant CNGs on oncogene and concordant change of gene expression, our results may be valuable for the design of CNV-based cancer diagnostic strategy.